Zhang, Han
(2017)
Price dependency and spillover effects in global crude oil markets.
PhD thesis, University of Nottingham.
Abstract
The content of this thesis is the result of a comprehensive study about global spot crude oil markets. Using a large data set including 32 crude varieties, this thesis analyzes price dependency, return and volatility spillover effects, and explores the driving forces behind such spillover effects.
The first major aim of the thesis is to detect the presence of structural breaks in the price dependency relationship found in the literature (Wlazlowski et al., 2011). Tests allowing for structural breaks are applied to re-examine unit root test, cointegration test and causality relationships. The results show significant structural breaks in all tests. However, the basic conclusions of unit root tests and cointegration tests are still valid in accounting for structural breaks, while the causality relationship is greatly influenced by the 2008 global crisis, making the conclusion of Wlazlowski et al. (2011) that the Russian Urals could serve as a potential benchmark invalid when using a longer sample period.
The second topic of investigation is the return and volatility spillover effects in the spot crude oil market. By applying a VAR forecast error variance decomposition method (Diebold and Yilmaz, 2012), various spillover measures are constructed. Static analysis shows that the majority of the total variance of the forecast error is explained by shocks across markets rather than by idiosyncratic shocks (87.1% for return and 80.57% for volatility), therefore supporting the integration hypothesis in the global crude oil market. Moreover, benchmark crudes play a key role in terms of return spillovers, possibly due to the pricing formula mechanism in the spot crude oil market. In terms of volatility, WTI behaves as a dominant transmitter. This is attributed to the 2008 global financial crisis, which originated in the United States. Dynamic analysis shows that return and volatility spillover indexes have different patterns. Return spillovers display gradual trends but no bursts, while volatility spillovers display clear bursts that correspond closely to events in the crude oil market. Further dynamic analysis was applied at individual, pairwise and group levels. Generally a time-varying characteristic of spillovers is found.
The third topic of analysis explores the driving forces behind spillover effects which are identified in the second chapter. Five categories of variables were selected to explain the spillover effects. These are international trade variables, fundamental economic variables, country risk variables, global risk factors and time trends. These variables are found to be more relevant for return spillovers than for volatility spillovers, and more relevant for non OPEC countries than for OPEC countries.
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